Neuromorphic Analog VLSI
This presentation is the property of its rightful owner.
Sponsored Links
1 / 16

Neuromorphic Analog VLSI PowerPoint PPT Presentation


  • 154 Views
  • Uploaded on
  • Presentation posted in: General

Neuromorphic Analog VLSI. David W. Graham West Virginia University Lane Department of Computer Science and Electrical Engineering. Neuromorphic Analog VLSI. Each word has meaning Neuromorphic Analog VLSI. Engineering Versus Biology. Core 2 Duo 65 watts 291 million transistors

Download Presentation

Neuromorphic Analog VLSI

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Neuromorphic analog vlsi

Neuromorphic Analog VLSI

David W. Graham

West Virginia University

Lane Department of Computer Science and Electrical Engineering


Neuromorphic analog vlsi

Neuromorphic Analog VLSI

Each word has meaning

Neuromorphic

Analog

VLSI


Engineering versus biology

Engineering Versus Biology

  • Core 2 Duo

  • 65 watts

  • 291 million transistors

  • >200nW/transistor

  • Brain

  • 10 watts

  • >100 billion neurons

  • ~100pW/neuron


Neuromorphic bio mimetic engineering

Neuromorphic/Bio-Mimetic Engineering

Neuromorphic/Bio-Mimetic Engineering – Using biology to inspire better engineering

High-quality processing

Low power consumption

  • Sensorimotor Systems

  • Intelligent robotics

  • Intelligent controls

  • Locomotive systems

  • Neurons

  • Systems that learn

  • Systems that adapt

  • Neural networks

  • Understanding biology

  • Silicon Retina

  • CMOS imagers

  • Intelligent imagers

  • Retinal implants

  • Audio Systems

  • Audio front ends

  • Signal processing systems

  • Hearing aids

  • Cochlear implants

  • Electronic Nose

  • “Sniff out” odors

  • Chemical sensors

  • Drug traffic control

  • Bio terror detection


Why neuromorphic engineering

Why Neuromorphic Engineering?

Interest in exploring

neuroscience

Interest in building

neurally inspired systems

Key Advantages

  • The dynamics is the system

  • What if our primitive gates were a neuron computation?

  • a synapse computation? a piece of dendritic cable?

  • Efficient implementations compute in their memory elements

  • – more efficient than directly reading all the coefficients

  • Precise systems out of imprecise parts


Biology and silicon devices

Biology and Silicon Devices

Similar physics of biological channels and p-n junctions

  • Drift and Diffusion equations form a built-in Barrier

  • (Vbi versus Nernst Potential)

  • Exponential distribution of particles

  • (Ions in biology and electrons/holes in silicon)

Both biological channels and transistors have a

gating mechanism that modulates a channel.


Comparison of scales

Comparison of scales

Molecules

Channels

Synapses

Neurons

CNS

Silicon

Parallel

Processors

Logic

Gates

Multipliers

PIII

Transistors

0.1nm

10nm

1mm

0.1mm

1cm

1m


Neuromorphic products

Neuromorphic Products

  • Neuromorphic Engineering is a relatively young field. However, it is already producing some very popular products.

  • Logitech Trackball

  • B.I.O.-Bugs and Robosapien

  • Neuromorphic Engineering is also helping to advance the field of neuroscience.


Where can we go

Where Can We Go?

Smart Embedded

Sensors

Low-Power Analog

  • Consumer Electronics

  • Implantable Devices

  • Subthreshold Design

  • Hearing Aids

  • Cochlear Implants

Analog Programmability

Powerful Mixed-Signal Systems

  • Provides digital features to the analog domain

  • Programmability

  • Accuracy

  • Reconfigurability

  • “Silicon Simulation”

Analog alleviates the burden of the digital

Bio-Inspired Systems


Why analog

Why Analog?

Much lower power than digital

Can perform many computations faster and more efficiently than digital

Follows the same physical laws as biological systems


Analog power savings

Analog Power Savings

G

G

e

e

n

n

e

e

'

'

s

s

L

L

a

a

w

w

1

0

0

W

D

D

S

S

P

P

P

P

o

o

w

w

e

e

r

r

C

C

A

A

D

D

S

S

P

P

P

P

o

o

w

w

e

e

r

r

1

W

1

0

m

W

P

r

o

g

r

a

m

m

a

b

l

e

Power Dissipated / MMAC

A

n

a

l

o

g

P

o

w

e

r

0

.

1

m

W

S

a

v

i

n

g

s

>

2

0

Y

e

a

r

L

e

a

p

1

W

i

n

T

e

c

h

n

o

l

o

g

y

1

0

n

W

1

9

8

0

1

9

9

0

2

0

0

0

2

0

1

0

2

0

2

0

2

0

3

0

Y

e

a

r

  • Gene’s Law

  • Power consumption of integrated circuits decreases exponentially over time

  • Follows Moore’s Law

  • Analog computation yields tremendous power savings equal to a >20 year leap in technology

  • FFT vs. Analog Cochlear Model

  • 32 subbands at 44.1kHz

  • FFT consumes ~5mW (audio-streamlined DSP)

  • Analog consumes <5μW

  • Analog power savings of >1000


Why vlsi

Why VLSI?

Cheaper (and easier to mass produce)

Smaller

Reduces power

Keeps everything contained

Reduces noise

Reduces coupling from the environment

Need a large number of transistors to perform real-world computations/tasks

Allows a high density or circuit elements (therefore, VLSI reduces costs)


Difference between discrete and vlsi design

Difference Between Discrete and VLSI Design


To summarize

To Summarize …

Good Things about Analog VLSI

Inexpensive

Compact

Power Efficient

Not So Good Things about Analog VLSI (not necessarily bad)

Limited to transistors and capacitors (and sometimes resistors if a very good reason)

Parasitics and device mismatch are big concerns

You are stuck with what you built/fabricated (no swapping parts out)

However, Neuromorphic Analog VLSI is all about how to cope with these “problems,” how to get around them, and how to use them as an advantage


Important considerations

Important Considerations

We will limit our discussion to CMOS technologies

No BJTs

Only MOSFETs

Therefore, we will discuss only silicon processes


Every story has a beginning

Every story has a beginning…

Looking at connections

with neurobiology

  • Begin at MOS device physics

  • Look at circuits using the device properties

  • Building small systems from circuits


  • Login